# Diabetic Complications and Genetic Variants in the Million Veterans Program

> **NIH VA I01** · VETERANS HEALTH ADMINISTRATION · 2024 · —

## Abstract

Diabetes (DM) complications are the major cause of its morbidity, mortality, and costs. MVP009 has
advanced understanding of the underlying genetics. Since DM care does not take advantage of progress in
genetics, we propose to use genetics to support both clinical translation and mechanistic discovery.
 In MVP009, we utilized highly specific phenotypes in genome-wide association studies (GWAS) of
(i) heart failure (HF) with preserved vs. reduced ejection fraction; (ii) hypoglycemia – severe (emergency visits)
and incidental (outpatient visits); (iii) kidney disease; and (iv) eye disease. We also found that although typical,
“juvenile-onset type 1 diabetes (T1D)” excludes military service, at least 10% of Veterans with presumed T2D
in MVP may have “adult onset T1D” – largely unrecognized. We now propose to extend these findings.
 Consistent with the Precision Medicine in Diabetes Consensus Report, our Aims target precision in
(i) diagnosis (genetic T1D vs. T2D), (ii) treatment [combining genetic with traditional risk factors (RF)], and (iii)
prognosis (epigenomic contributions to complications) – to incorporate genetics so that care can be more
accurate and individualized, and identify mechanisms that can lead to discovery of new treatments.
 Aim 1: Assess the contributions of T1D and T2D genetic loads to the clinical characteristics
and disease trajectories of people presumed to have T2D. We will model multiethnic genetic risk with T1D
and T2D polygenic risk scores (PRS, with multiethnic data from large recent studies); each MVP Veteran will
have both a T1D and a T2D PRS. Outcomes will include incident DM, and the disease trajectory: age and BMI
at onset, time to insulin Rx, and ketoacidosis and hypoglycemia. We will evaluate the utility of the PRS to
identify Veterans with DM who would benefit from definitive T1D testing and/or early use of insulin.
 Aim 2: Assess the combined contributions of genetic/nongenetic RF to development of
complications. (SubAim a) Identify effect modifications between RF and complications. Genetic
interaction analyses will include lifestyle, demographics, and comorbidities (e.g., blood pressure, HbA1c), as
modifiers of the risk of complications conferred by disease loci and PRS. We will use both hypothesis-testing
approaches for known loci and PRS, and hypothesis-generating approaches (using genome-wide G×E
modeling) to examine interactions associated with diabetic eye disease (DED), kidney disease (DKD), HF, and
hypoglycemia, and causal associations using state-of-the-art Mendelian Randomization (MR), including
multivariable and mediation MR. (SubAim b) Develop and test predictive models. We will use summary
statistics from the MVP GWAS and the literature, to develop separate PRS using the “best practice” recent
method, for DED, DKD, HF, and hypoglycemia, and PheWAS with the PRSs to elucidate previously unknown
RFs. Utilizing the PRS, PheWAS, information from SubAim (a), clinical RF, and treatments, we will develop
g...

## Key facts

- **NIH application ID:** 10911023
- **Project number:** 5I01BX005831-03
- **Recipient organization:** VETERANS HEALTH ADMINISTRATION
- **Principal Investigator:** LAWRENCE S PHILLIPS
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2024
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2022-07-01 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10911023

## Citation

> US National Institutes of Health, RePORTER application 10911023, Diabetic Complications and Genetic Variants in the Million Veterans Program (5I01BX005831-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10911023. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*